{
 "cells": [
  {
   "cell_type": "code",
   "execution_count": 3,
   "metadata": {},
   "outputs": [],
   "source": [
    "import numpy as np"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 5,
   "metadata": {},
   "outputs": [],
   "source": [
    "vvi = np.load('opt_v_table_vi.npy')\n",
    "vpi = np.load('opt_v_table_pi.npy')\n",
    "qvi = np.load('opt_q_table_vi.npy')\n",
    "qpi = np.load('opt_q_table_pi.npy')\n",
    "pvi = np.load('opt_policy_vi.npy')\n",
    "ppi = np.load('opt_policy_pi.npy')"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 6,
   "metadata": {},
   "outputs": [],
   "source": [
    "choice_vi=np.zeros((20, 6))\n",
    "for p in range(19, 0, -1):\n",
    "    for v in range(6):\n",
    "        choice_vi[p][v] = int(np.argmax(qvi[p][v]))\n",
    "\n",
    "choice_pi=np.zeros((20, 6))\n",
    "for p in range(20):\n",
    "    for v in range(6):\n",
    "        choice_pi[p][v] = int(np.argmax(qpi[p][v]))"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 7,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
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      "\n",
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      "  [nan nan nan 0.000000000 0.000000000]]]\n"
     ]
    },
    {
     "name": "stderr",
     "output_type": "stream",
     "text": [
      "C:\\Users\\simon.chauvin\\AppData\\Local\\Continuum\\anaconda3\\envs\\tensorflow\\lib\\site-packages\\ipykernel\\__main__.py:9: RuntimeWarning: invalid value encountered in subtract\n"
     ]
    }
   ],
   "source": [
    "np.set_printoptions(formatter={'float': lambda x: \"{0:0.9f}\".format(x)})\n",
    "\n",
    "diffv = vvi - vpi\n",
    "print(diffv)\n",
    "\n",
    "diffp = pvi - ppi\n",
    "print(diffp)\n",
    "\n",
    "diffq = qvi - qpi\n",
    "print(diffq)\n",
    "# (vvi == vpi).all()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 8,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "image/png": "iVBORw0KGgoAAAANSUhEUgAAAHAAAAD8CAYAAACvkiDoAAAABHNCSVQICAgIfAhkiAAAAAlwSFlz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\n6JwQ6JwQ6JwQ6JwQ6JwQ6JwQ6Jz/AfFc2Bj//MyGAAAAAElFTkSuQmCC\n",
      "text/plain": [
       "<matplotlib.figure.Figure at 0x2ed4eadbcc0>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "import matplotlib.pyplot as plt\n",
    "plt.imshow(vvi)\n",
    "plt.imshow(choice_vi)\n",
    "plt.show()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 9,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "image/png": 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DMNO+v84Xolpv+9w5kp/CvKNvx5UWXn+YvpMK4NNCyKAoNxzqOqWUNhxuFfkGUTnlcbdb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\n",
      "text/plain": [
       "<matplotlib.figure.Figure at 0x2ed515f5780>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "import matplotlib.pyplot as plt\n",
    "import numpy as np\n",
    "from mpl_toolkits.axes_grid1 import make_axes_locatable\n",
    "from matplotlib.ticker import MultipleLocator\n",
    "from matplotlib.lines import Line2D\n",
    "\n",
    "fig, (ax1, ax2, ax3, ax4) = plt.subplots(ncols=4, figsize=(11,10))\n",
    "fig.suptitle('Optimal Value Function and Optimal Policy \\n for Policy_Iteration and Value_Iteration', fontsize=20)\n",
    "cmap = plt.cm.viridis\n",
    "\n",
    "# Values\n",
    "ax1.set_title('Values of states - PI')\n",
    "im1 = ax1.imshow(vpi, aspect='auto', cmap=cmap)\n",
    "divider1 = make_axes_locatable(ax1)\n",
    "cax1 = divider1.append_axes(\"right\", size=\"20%\", pad=0.15)\n",
    "cbar1 = plt.colorbar(im1, cax=cax1, ticks=MultipleLocator(10), format=\"%.2f\")\n",
    "ax1.set_ylim(0,20)\n",
    "\n",
    "ax2.set_title('Values of states - VI')\n",
    "im2 = ax2.imshow(vvi, aspect='auto', cmap=cmap)\n",
    "divider2 = make_axes_locatable(ax2)\n",
    "cax2 = divider2.append_axes(\"right\", size=\"20%\", pad=0.15)\n",
    "cbar2 = plt.colorbar(im2, cax=cax2, ticks=MultipleLocator(10), format=\"%.2f\")\n",
    "ax2.set_ylim(0,20)\n",
    "\n",
    "cmap = plt.cm.tab20b\n",
    "\n",
    "# Policies\n",
    "ax3.set_title('Best action - PI')\n",
    "# Display image, `aspect='auto'` makes it fill the whole `axes` (ax3)\n",
    "im3 = ax3.imshow(choice_pi, origin='lower', cmap=cmap, aspect='auto')\n",
    "# Create divider for existing axes instance\n",
    "# divider3 = make_axes_locatable(ax3)\n",
    "# Append axes to the right of ax3, with 20% width of ax3\n",
    "# cax3 = divider3.append_axes(\"right\", size=\"20%\", pad=0.15)\n",
    "# Create colorbar in the appended axes\n",
    "# Tick locations can be set with the kwarg `ticks`\n",
    "# and the format of the ticklabels with kwarg `format`\n",
    "# cbar3 = plt.colorbar(im3, cax=cax3, ticks=MultipleLocator(1), format=\"%.2f\")\n",
    "\n",
    "ax4.set_title('Best action - VI')\n",
    "im4 = ax4.imshow(choice_vi, origin='lower', cmap=cmap, aspect='auto')\n",
    "# divider4 = make_axes_locatable(ax4)\n",
    "# cax4 = divider4.append_axes(\"right\", size=\"20%\", pad=0.15)\n",
    "# cbar4 = plt.colorbar(im4, cax=cax4, ticks=MultipleLocator(1), format=\"%.2f\")\n",
    "\n",
    "\n",
    "plt.tight_layout()\n",
    "# Make space for title\n",
    "plt.subplots_adjust(top=0.85)\n",
    "\n",
    "for axis in [ax1, ax2, ax3, ax4]:\n",
    "    axis.set_xlabel('velocity')\n",
    "    axis.set_ylabel('position')\n",
    "    axis.grid(color='k', linestyle='-', linewidth=1)\n",
    "    axis.yaxis.set_major_locator(MultipleLocator(1))\n",
    "    axis.xaxis.set_major_locator(MultipleLocator(1))\n",
    "\n",
    "# legend\n",
    "custom_lines = [Line2D([0], [0], color=cmap(0.5), lw=4),\n",
    "                Line2D([0], [0], color=cmap(0.25), lw=4),\n",
    "                Line2D([0], [0], color=cmap(0), lw=4),\n",
    "                Line2D([0], [0], color=cmap(0.75), lw=4),\n",
    "                Line2D([0], [0], color=cmap(1.0), lw=4)\n",
    "               ]\n",
    "\n",
    "actions_list = [\"speed_up_up\", \"speed_up\", \"no_change\", \"slow_down\", \"slow_down_down\"]\n",
    "fig.legend(custom_lines, actions_list)\n",
    "\n",
    "plt.savefig(\"map_values_policies.png\", dpi=1000)\n",
    "# plt.savefig('map_values_policies.eps', format='eps', dpi=1000)\n",
    "\n",
    "plt.show()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {},
   "outputs": [],
   "source": []
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {},
   "outputs": [],
   "source": []
  }
 ],
 "metadata": {
  "anaconda-cloud": {},
  "kernelspec": {
   "display_name": "integration",
   "language": "python",
   "name": "integration"
  },
  "language_info": {
   "codemirror_mode": {
    "name": "ipython",
    "version": 3
   },
   "file_extension": ".py",
   "mimetype": "text/x-python",
   "name": "python",
   "nbconvert_exporter": "python",
   "pygments_lexer": "ipython3",
   "version": "3.5.4"
  }
 },
 "nbformat": 4,
 "nbformat_minor": 2
}
